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Record W3091870535 · doi:10.1021/acsami.0c14987

Monolithic Spiropyran-Based Porous Polysilsesquioxanes with Stimulus-Responsive Properties

2020· article· en· W3091870535 on OpenAlexaff
Daniel Euchler, Caroline R. Ehgartner, Nicola Hüsing, Andrea Feinle

Bibliographic record

VenueACS Applied Materials & Interfaces · 2020
Typearticle
Languageen
FieldMaterials Science
TopicPhotochromic and Fluorescence Chemistry
Canadian institutionsMcMaster University
FundersAustrian Science Fund
KeywordsSpiropyranSilsesquioxaneMaterials sciencePorosityMerocyanineWettingPhotochemistryCovalent bondChemical engineeringPolymerMonolithProtonationIrradiationPhotochromismNanotechnologyOrganic chemistryComposite materialChemistryCatalysis

Abstract

fetched live from OpenAlex

Dynamic materials comprising spiropyrans have emerged as one of the most interesting and promising class of stimulus-responsive materials. Spiropyrans are often embedded in polymer matrices; their covalent attachment into porous monolithic silsesquioxane frameworks, however, is virtually unexplored. We demonstrate that a silylated spiropyran derivative can be covalently incorporated into ultralight silsesquioxane-based bulk materials by a two-step co-condensation sol-gel approach without restricting its conformational freedom and thus its stimulus-responsive properties. UV-vis measurements prove the conversion of the colorless closed-ring form of the spiropyran molecule into its highly colored purple isomer or the yellow colored protonated structure thereof. The transformation can be triggered simply by irradiation of the spiropyran-containing silsesquioxane monolith with UV or visible light or by the pH value of the chemical environment. A strong dependence of the surface polarity and water wettability on the prevalent isomer was observed. The contact angle of a water droplet on the monolithic surface can be altered from 146 to 100° by irradiation of the monolith with UV light for 3 min. Additionally, the prepared materials possess high specific surface areas, low bulk densities, and porosities of up to 84%.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.213
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations33
Published2020
Admission routes1
Has abstractyes

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